The approaches described in this section are approaches that could be pursued, but not necessarily approaches that have been previously conceived or pursued. Therefore, unless otherwise indicated, it should not be assumed that any of the approaches described in this section qualify as prior art merely by virtue of their inclusion in this section.
Many datacenters undergo two major types of transformations over time. First, a typical datacenter experiences significant growth with an ever increasing number of software deployments. Second, the software and hardware resources within the datacenter are typically improved or updated with advancements in technology or changes to the underlying deployment models. These transformations may lead to resource deployments that are siloed, dispersed, varied and complex. Some enterprise deployments have thousands of software applications and hardware resources. The ever-increasing and divergent nature of software and hardware deployments within a datacenter may lead to significant challenges in updating and maintaining system resources.
One challenge that datacenter administrators face is maintaining optimal configurations across a large number of software and hardware resources. As resources are updated and improved over time, some targets may begin to drift from business best practice guidelines or other gold standards. For example, some resources may not receive recommended updates or may have updates applied that are not part of the gold standard. Resource drift may cause complex system to function incorrectly or may otherwise adversely affect system functionality and performance. Therefore, administrators are tasked with minimizing and mitigating the effects of resource drift. In large datacenter environments, drift may be particularly difficult for administrators to manage and contain given the number of different resources and configurations.